Internal Error meaning

What’s the meaning of this error and how do I fix it?
[TensorRT] INTERNAL ERROR: Assertion failed: mg.nodes[mg.regionIndices[outputRegion]].size == mg.nodes[mg.regionIndices[inputRegion]].size

Hi,

Could you please share the script and model file along with error log so we can help better?
Also, can you provide details on the platforms you are using:
o Linux distro and version
o GPU type
o Nvidia driver version
o CUDA version
o CUDNN version
o Python version [if using python]
o Tensorflow and PyTorch version
o TensorRT version

Thanks

Hi,

The issue can be reproduced in Google Colab at the following link: https://colab.research.google.com/drive/1lF2hPp36Su8HVIE30f3EkSrAxIohgE2J

Please follow the instructions in the notebook to reproduce the error.

The environment can be explored in the notebook, but as far as I can tell it’s the following:

  • Ubuntu 18.04
  • Nvidia T4
  • Driver Version: 418.67
  • CUDA Version: 10.1
  • Cudnn V10.0.130
  • Python 3.6.9
  • Pytorch 1.3.1
  • TensorRT 7.0.0

I also have a question about the Python API: I tried both builder.max_workspace_size and builderconfig.max_workspace_size for setting the max workspace size, but always when I finish building the engine successfully and check the engine.max_workspace_size property, it’s 0. Is that normal, or am I failing to set the workspace size correctly?

Hi,

torch2trt converter has limited coverage of TensorRT / PyTorch. Issue might be due to dynamic input in your model.
Can you try converting the pytorch model into onnx and then using onnx2trt to generate the TRT engine file?

Thanks

I’m not quite using torch2trt, but my heavily modified version at https://github.com/akababa/torch2trt/. My goal is to add dynamic input size support to convert models such as GPT-2 and eventually upstream it into the main torch2trt repository.
I’m not getting the previous error anymore (not sure how/if I solved it), and I successfully converted the gpt2-small model, but now tensorrt is crashing when I try to convert gpt2-medium. I think it has something to do with the extremely long log messages that look like the following:

[TensorRT] VERBOSE: *************** Autotuning format combination: Bool(1,(+ (# 3 (SHAPE past)) (# 0 (SHAPE input_ids))),(* (+ (# 3 (SHAPE past)) (# 0 (SHAPE input_ids))) (- (+ (# 3 (SHAPE past)) (# 0 (SHAPE input_ids))) (# 3 (SHAPE past))))), Half(1,(+ (BROADCAST_SIZE (BROADCAST_SIZE (# 0 (SHAPE input_ids)) (BROADCAST_SIZE (# 0 (SHAPE input_ids)) (- (+ (# 3 (SHAPE past)) (# 0 (SHAPE input_ids))) (# 3 (SHAPE past))))) (BROADCAST_SIZE (BROADCAST_SIZE (# 0 (SHAPE input_ids)) (BROADCAST_SIZE (# 0 (SHAPE input_ids)) (- (+ (# 3 (SHAPE past)) (# 0 (SHAPE input_ids))) (# 3 (SHAPE past))))) (- (+ (# 3 (SHAPE past)) (# 0 (SHAPE input_ids))) (# 3 (SHAPE past))))) (# 3 (SHAPE past))),(* (BROADCAST_SIZE (BROADCAST_SIZE (# 0 (SHAPE input_ids)) (BROADCAST_SIZE (# 0 (SHAPE input_ids)) (- (+ (# 3 (SHAPE past)) (# 0 (SHAPE input_ids))) (# 3 (SHAPE past))))) (BROADCAST_SIZE (BROADCAST_SIZE (# 0 (SHAPE input_ids)) (BROADCAST_SIZE (# 0 (SHAPE input_ids)) (- (+ (# 3 (SHAPE past)) (# 0 (SHAPE input_ids))) (# 3 (SHAPE past))))) (- (+ (# 3 (SHAPE past)) (# 0 (SHAPE input_ids))) (# 3 (SHAPE past))))) (+ (BROADCAST_SIZE (BROADCAST_SIZE (# 0 (SHAPE input_ids)) (BROADCAST_SIZE (# 0 (SHAPE input_ids)) (- (+ (# 3 (SHAPE past)) (# 0 (SHAPE input_ids))) (# 3 (SHAPE past))))) (BROADCAST_SIZE (BROADCAST_SIZE (# 0 (SHAPE input_ids)) (BROADCAST_SIZE (# 0 (SHAPE input_ids)) (- (+ (# 3 (SHAPE past)) (# 0 (SHAPE input_ids))) (# 3 (SHAPE past))))) (- (+ (# 3 (SHAPE past)) (# 0 (SHAPE input_ids))) (# 3 (SHAPE past))))) (# 3 (SHAPE past))))) -> Half(1,(BROADCAST_SIZE (+ (# 3 (SHAPE past)) (# 0 (SHAPE input_ids))) (+ (BROADCAST_SIZE (BROADCAST_SIZE (# 0 (SHAPE input_ids)) (BROADCAST_SIZE (# 0 (SHAPE input_ids)) (- (+ (# 3 (SHAPE past)) (# 0 (SHAPE input_ids))) (# 3 (SHAPE past))))) (BROADCAST_SIZE (BROADCAST_SIZE (# 0 (SHAPE input_ids)) (BROADCAST_SIZE (# 0 (SHAPE input_ids)) (- (+ (# 3 (SHAPE past)) (# 0 (SHAPE input_ids))) (# 3 (SHAPE past))))) (- (+ (# 3 (SHAPE past)) (# 0 (SHAPE input_ids))) (# 3 (SHAPE past))))) (# 3 (SHAPE past)))),(* (BROADCAST_SIZE (+ (# 3 (SHAPE past)) (# 0 (SHAPE input_ids))) (+ (BROADCAST_SIZE (BROADCAST_SIZE (# 0 (SHAPE input_ids)) (BROADCAST_SIZE (# 0 (SHAPE input_ids)) (- (+ (# 3 (SHAPE past)) (# 0 (SHAPE input_ids))) (# 3 (SHAPE past))))) (BROADCAST_SIZE (BROADCAST_SIZE (# 0 (SHAPE input_ids)) (BROADCAST_SIZE (# 0 (SHAPE input_ids)) (- (+ (# 3 (SHAPE past)) (# 0 (SHAPE input_ids))) (# 3 (SHAPE past))))) (- (+ (# 3 (SHAPE past)) (# 0 (SHAPE input_ids))) (# 3 (SHAPE past))))) (# 3 (SHAPE past)))) (BROADCAST_SIZE (BROADCAST_SIZE (BROADCAST_SIZE (# 0 (SHAPE input_ids)) (BROADCAST_SIZE (# 0 (SHAPE input_ids)) (- (+ (# 3 (SHAPE past)) (# 0 (SHAPE input_ids))) (# 3 (SHAPE past))))) (BROADCAST_SIZE (BROADCAST_SIZE (# 0 (SHAPE input_ids)) (BROADCAST_SIZE (# 0 (SHAPE input_ids)) (- (+ (# 3 (SHAPE past)) (# 0 (SHAPE input_ids))) (# 3 (SHAPE past))))) (- (+ (# 3 (SHAPE past)) (# 0 (SHAPE input_ids))) (# 3 (SHAPE past))))) (- (+ (# 3 (SHAPE past)) (# 0 (SHAPE input_ids))) (# 3 (SHAPE past)))))) ***************
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past)) (# 0 (SHAPE input_ids))) (# 3 (SHAPE past))))) (- (+ (# 3 (SHAPE past)) (# 0 (SHAPE input_ids))) (# 3 (SHAPE past))))) (BROADCAST_SIZE (BROADCAST_SIZE (BROADCAST_SIZE (# 0 (SHAPE input_ids)) (BROADCAST_SIZE (# 0 (SHAPE input_ids)) (- (+ (# 3 (SHAPE past)) (# 0 (SHAPE input_ids))) (# 3 (SHAPE past))))) (BROADCAST_SIZE (BROADCAST_SIZE (# 0 (SHAPE input_ids)) (BROADCAST_SIZE (# 0 (SHAPE input_ids)) (- (+ (# 3 (SHAPE past)) (# 0 (SHAPE input_ids))) (# 3 (SHAPE past))))) (- (+ (# 3 (SHAPE past)) (# 0 (SHAPE input_ids))) (# 3 (SHAPE past))))) (- (+ (# 3 (SHAPE past)) (# 0 (SHAPE input_ids))) (# 3 (SHAPE past)))))) (- (+ (# 3 (SHAPE past)) (# 0 (SHAPE input_ids))) (# 3 (SHAPE past)))) (BROADCAST_SIZE (BROADCAST_SIZE (BROADCAST_SIZE (BROADCAST_SIZE (BROADCAST_SIZE (# 0 (SHAPE input_ids)) (BROADCAST_SIZE (# 0 (SHAPE input_ids)) (- (+ (# 3 (SHAPE past)) (# 0 (SHAPE input_ids))) (# 3 (SHAPE past))))) (BROADCAST_SIZE (BROADCAST_SIZE (# 0 (SHAPE input_ids)) (BROADCAST_SIZE (# 0 (SHAPE input_ids)) (- (+ (# 3 (SHAPE past)) (# 0 (SHAPE input_ids))) (# 3 (SHAPE past))))) (- (+ (# 3 (SHAPE past)) (# 0 (SHAPE input_ids))) (# 3 (SHAPE past))))) (BROADCAST_SIZE (BROADCAST_SIZE (BROADCAST_SIZE (# 0 (SHAPE input_ids)) (BROADCAST_SIZE (# 0 (SHAPE input_ids)) (- (+ (# 3 (SHAPE past)) (# 0 (SHAPE input_ids))) (# 3 (SHAPE past))))) (BROADCAST_SIZE (BROADCAST_SIZE (# 0 (SHAPE input_ids)) (BROADCAST_SIZE (# 0 (SHAPE input_ids)) (- (+ (# 3

My guess is that this is caused by many repeated operations involving broadcasting, which confuses TRT’s shape inference engine because it doesn’t realize that the input shapes are left unchanged after broadcasting. Do you have any tips for reducing this problem or writing ops in a way that helps TRT do shape inference?

So it seems I’ve solved the above problem as well now, although now I’m getting

[TensorRT] ERROR: ../rtSafe/safeRuntime.cpp (25) - Cuda Error in allocate: 2 (out of memory)

at the end of building despite setting the max_workspace_size to 1<<30 in the IBuilderConfig. Should I set this value even higher, or am I doing something incorrectly?

Much thanks!

Yes, you can try increasing the max_workspace_size.
Also, check if there is any other process running on same GPU which is causing the “Out of memory” issue.

Thanks